Since Spark isĪ general purpose cluster computing system there are many potentialĪpplications for extensions (e.g. interfaces to custom machine learning
Learning interfaces are available to extension packages. The facilities used internally by sparklyr for its dplyr and machine We’ll assume in each case that the relationshipīetween mpg and each of our features is linear.įunction( e) broom ::tidy(lm( Petal_Width ~ Petal_Length, e)),Ĭolumns = c( "term ", "estimate ", "std.error ", "statistic ", "p.value "), We’ll use the built-in mtcarsĭataset, and see if we can predict a car’s fuel consumption ( mpg)īased on its weight ( wt), and the number of cylinders the engineĬontains ( cyl). High-level APIs built on top of DataFrames that help you create and tune You can orchestrate machine learning algorithms in a Spark cluster viaįunctions within sparklyr. Use dbGetQuery() to execute SQL and return the result as an R data It’s also possible to execute SQL queries directly against tables withinĪ Spark cluster.
Select( playerID, yearID, teamID, G, AB : H) % >%
0 kommentar(er)
